numpy.asanyarray
-
numpy.asanyarray(a, dtype=None, order=None)[source] -
Convert the input to an ndarray, but pass ndarray subclasses through.
- Parameters
-
-
aarray_like -
Input data, in any form that can be converted to an array. This includes scalars, lists, lists of tuples, tuples, tuples of tuples, tuples of lists, and ndarrays.
-
dtypedata-type, optional -
By default, the data-type is inferred from the input data.
-
order{‘C’, ‘F’}, optional -
Whether to use row-major (C-style) or column-major (Fortran-style) memory representation. Defaults to ‘C’.
-
- Returns
-
-
outndarray or an ndarray subclass -
Array interpretation of
a. Ifais an ndarray or a subclass of ndarray, it is returned as-is and no copy is performed.
-
See also
-
asarray -
Similar function which always returns ndarrays.
-
ascontiguousarray -
Convert input to a contiguous array.
-
asfarray -
Convert input to a floating point ndarray.
-
asfortranarray -
Convert input to an ndarray with column-major memory order.
-
asarray_chkfinite -
Similar function which checks input for NaNs and Infs.
-
fromiter -
Create an array from an iterator.
-
fromfunction -
Construct an array by executing a function on grid positions.
Examples
Convert a list into an array:
>>> a = [1, 2] >>> np.asanyarray(a) array([1, 2])
Instances of
ndarraysubclasses are passed through as-is:>>> a = np.array([(1.0, 2), (3.0, 4)], dtype='f4,i4').view(np.recarray) >>> np.asanyarray(a) is a True
© 2005–2020 NumPy Developers
Licensed under the 3-clause BSD License.
https://numpy.org/doc/1.18/reference/generated/numpy.asanyarray.html